| thon | |
| import requests | |
| import torch | |
| from PIL import Image | |
| from transformers import AlignProcessor, AlignModel | |
| processor = AlignProcessor.from_pretrained("kakaobrain/align-base") | |
| model = AlignModel.from_pretrained("kakaobrain/align-base") | |
| url = "http://images.cocodataset.org/val2017/000000039769.jpg" | |
| image = Image.open(requests.get(url, stream=True).raw) | |
| candidate_labels = ["an image of a cat", "an image of a dog"] | |
| inputs = processor(text=candidate_labels, images=image, return_tensors="pt") | |
| with torch.no_grad(): | |
| outputs = model(**inputs) | |
| this is the image-text similarity score | |
| logits_per_image = outputs.logits_per_image | |
| we can take the softmax to get the label probabilities | |
| probs = logits_per_image.softmax(dim=1) | |
| print(probs) | |
| Resources | |
| A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with ALIGN. |